Model izračuna čimbenika spremnosti za industriju 4.0 usmjerenoga na projektiranje tehnoloških procesa

doctoral thesis

• Title (english): A model for calculating the process planning oriented industry 4.0 readiness factor
• Author: Maja Trstenjak
• Mentor: Tihomir Opetuk (mentor)
• Committee member: Hrvoje Cajner (predsjednik povjerenstva)
• Committee member: Miro Hegedić (član povjerenstva)
• Committee member: Goran Šimunović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Mechanical Engineering and Naval Architecture; Zagreb
• Defense date and country: 2021-03-05, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mechanical Engineering
• Universal decimal classification (UDC): 658 - Business management, administration. Commercial organization

Abstract

Koncept Industrije 4.0 čine integrirani alati kako bi se stvorila fleksibilna proizvodnja s visokim stupnjem autonomnosti. Digitalizacija, kao dio koncepta Industrije 4.0 je ključan dio prilagodbe trendovima na tržištu za održanje konkurentnosti tvrtki. To je viša razina informatičkih znanja i investicija, na koje male i srednje tvrtke često nisu spremne dok s druge strane njihovi veći konkurenti započinju s implementacijom koncepta te tako povećavaju prednost na tržištu. U okviru ove disertacije poseban naglasak je stavljen na projektiranje tehnoloških procesa, za koji je razvijen izračuna čimbenika spremnosti (eng. readiness factor) za prihvaćanje koncepta Industrije 4.0 pomoću metoda višekriterijskog odlučivanja i optimiranja. Budući da se radi o evaluaciji trenutnog stanja na temelju različitih kriterija, sustavi za potporu odlučivanju prepoznati su kao jedan od alata. Izračun čimbenika spremnosti tvrtki pomaže u definiciji optimalnog strateškog plana ka prihvaćanju koncepta Industrije 4.0, što je od neizmjerne važnosti zbog izazova koji nosi implementacija koncepta. Model za izračun čimbenika spremnosti proveden je pomoću metode analitičkog hijerarhijskog procesa, verificiran je analizom osjetljivosti, potvrđen simulacijom i primijenjen na studiji slučaja u tvrtki iz ciljane grupe.

Abstract (english)

Industry 4.0 concept is based on integrated tools in order to create flexible and highly autonomous manufacturing. Digitization, as part of the Industry 4.0 concept, is a key part of adapting to market trends to maintain competitiveness. This is a higher level of IT knowledge and investment, to which small and medium-sized companies are often not ready for, while, on the other hand, their larger competitors have already started implementing the concept and thus increase their market advantage. In this dissertation, special emphasis will be placed on the design of technological processes, for which a Industry 4.0 readiness factor calculation model using multicriteria decision-making and optimization methods will be developed. Nature of this problem is evaluation of the current situation based on different criteria, so decision support systems have been identified as one of the tools. The calculation of the company's readiness factor helps to define an optimal strategic plan towards the acceptance of the Industry 4.0 concept, which is of immense importance due to the challenges posed by the implementation of the concept. The model for readiness factor calculation was developed by use of analytic hierarchical process method, verified by sensitivity analysis, confirmed by simulation and applied in a case study.

• Keywords: projektiranje tehnoloških procesa; industrija 4.0; analitički hijerarhijski proces; multikriterijsko optimiranje; digitalizacija; CAPP
• Keywords (english): process planning; Industry 4.0; analytic hierarchy process; multi-criteria optimization; digitization; CAPP
• Language: croatian
• URN:NBN: urn:nbn:hr:235:330072
• Study programme: Title: Mechanical Engineering and Naval Architecture; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, područje tehničkih znanosti (doktor/doktorica znanosti, područje tehničkih znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2021-05-21 07:34:46